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Data Science for Economics and Finance [2021]
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Data Science Technologies in Economics and Finance: A Gentle Walk-In
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Supervised Learning for the Prediction of Firm Dynamics
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Opening the Black Box: Machine Learning Interpretability and Inference Tools with an Application to Economic Forecasting
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Machine Learning for Financial Stability
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Sharpening the Accuracy of Credit Scoring Models with Machine Learning Algorithms
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Classifying Counterparty Sector in EMIR Data
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Massive Data Analytics for Macroeconomic Nowcasting
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New Data Sources for Central Banks
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Sentiment Analysis of Financial News: Mechanics and Statistics
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Semi-supervised Text Mining for Monitoring the News About the ESG Performance of Companies
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Extraction and Representation of Financial Entities from Text
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Quantifying News Narratives to Predict Movements in Market Risk
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Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets?
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Network Analysis for Economics and Finance: An Application to Firm Ownership